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EVENTS

RESEARCH

AN EMPIRICAL APPROACH TO UNDERSTANDING USERS' FAKE NEWS IDENTIFICATION ON SOCIAL MEDIA

[ARTICLE] This study explores factors influencing social media users' identification of fake news, finding that expertise in social media use and verification behavior positively impact fake news identification, while trust in social media reduces it.

by Karine Aoun Barakat (ESSEC Business School), Amal Dabbous, Abbas Tarhini 

Purpose
During the past few years, the rise in social media use for information purposes in the absence of adequate control mechanisms has led to growing concerns about the reliability of the information in circulation and increased the presence of fake news. While this topic has recently gained researchers' attention, very little is known about users' fake news identification behavior. Hence, the purpose of this study is to understand the factors that contribute to individuals' identification of fake news on social media.

Design/methodology/approach
This study employs a quantitative approach and proposes a behavioral model that explores the factors influencing users' identification of fake news on social media. It relies on data collected from a sample of 211 social media users which is tested using SEM.

Findings
The findings show that expertise in social media use and verification behavior have a positive impact on fake news identification, while trust in social media as an information channel decreases this identification behavior. Furthermore, results establish the mediating role of social media information trust and verification behavior.

Originality/value
The present study enhances our understanding of social media users' fake news identification by presenting a behavioral model. It is one of the few that focuses on the individual and argues that by identifying the factors that reinforce users' fake news identification behavior on social media, this type of misinformation can be reduced. It offers several theoretical and practical contributions.

[Please read the research paper here]

Research list
MULTIVARIATE VOLATILITY FORECASTS FOR STOCK MARKET INDICES

MULTIVARIATE VOLATILITY FORECASTS FOR STOCK MARKET INDICES

[ARTICLE] This study forecasts realized variance for major international stock market indices, incorporating jump, continuous, and option-implied variance components, using ...
DYNAMICS OF VARIANCE RISK PREMIA: A NEW MODEL FOR DISENTANGLING THE PRICE OF RISK

DYNAMICS OF VARIANCE RISK PREMIA: A NEW MODEL FOR DISENTANGLING THE PRICE OF RISK

[ARTICLE] This paper presents a dynamic model for the variance risk premium that separates the continuous component from jump impacts, ...
MINIMUM COST NETWORK DESIGN IN STRATEGIC ALLIANCES

MINIMUM COST NETWORK DESIGN IN STRATEGIC ALLIANCES

[ARTICLE] This paper investigates the impact of transaction costs on the viability of strategic alliances in service network design, highlighting ...
FROM DATA TO CAUSES II: COMPARING APPROACHES TO PANEL DATA ANALYSIS

FROM DATA TO CAUSES II: COMPARING APPROACHES TO PANEL DATA ANALYSIS

[ARTICLE] This article compares various panel data methods, highlighting the benefits of the general cross-lagged model (GCLM) over static models ...
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